Thesis topics

From GHER

The following list of Ph.D. Thesis topics proposed at GHER is not exhaustive and depending on the student's interest and the ongoing research projects additional themes can be defined.

Our objective is to propose subjects which are stronly linked to ongoing research efforts at international level (see our projects) and make sure students can collaborate with collegues at other universities or research centers. This has also the advantage of ensure adequate access to recent data.

Studends are welcomed to apply a Ph.D. position at any moment and depending on the schedules and interests of the student, applications to FRIA or FNR-FNRS will be prepared. For Ph.D positions offered within projects, you can also consult
[1] or Jobs

Data Analysis methodologies

Multivariate approaches

Whereas classical optimal interpolation allows naturally for the analysis of several variables (such as nitrate and phosphates) in a joint matter, exploiting covariances between variables, our spatial gridding tool DIVA only can proceed a singe variable at a time. Though allowing for more realistic spatial covariances than classical optimal interpolation DIVA is therefore however underexploiting possible links between variables. The work will consist in adding this feature to DIVA (by an iterative approach) and apply it to the creation of biochemical climatologies in the Mediterranean or Black Sea. If sufficient data and correlations with other parameters reliable, the regime shifts in deep water formations in the eastern Mediterranean could be revisited.

New FEM DIVA solver in ND

The present version of DIVA, also exploited in
Diva on web, is using a robust but outdated finite element solver in 2D. In order to prepare for 3D or 4D applications, the use of a general FEM framework should be analysed such as GETDP with its mesh generator gmsh. The implementation should be portable and parallelize and show the benefit of performing 3D analyses compared to 2D versions. Oceanographic applications will then concentrate on deep ventilation processes, something which is difficult to represent with horizontal analysis alone.

Multiscale DINEOF-OI

DINEOF is a widely used tool for analysing satellite data with missing data. Not only does the tool provide estimates of the missing data but also the structure of dynamic modes from an EOF (empirical orthogonal function) analysis. To further exploit the dynamic information found in these modes, a scale selective analysis can be wrapped into the filling step, so as to provide modes for specific scales. This is particularly interesting for understanding relationships with climatic modes for example. Here several strategies for decomposing and filterging should be tested and validated on long times series of temperature fields. High frequency images in combination with low frequency passes will then allow for a better specification of the features at various time and space scales. An application to a tidally dominated sea and an application to a mesoscale dominated region will be used to check the sensitivity of the method. If successful it would allow to provide guidance for the specifications of covariances matrices used in data assimilation.

Developments in numerical modelling

Ocean Sound

Coupled ocean atmosphere model with improved bulk exchanges

Simulation of sea surface temperature and circulation in the Bay of Calvi

New Data Assimilation schemes

Non linear aspects

Multiscale aspects

Oceanographic themes

Here the emphasis is rather on using the tools mentionned above to look at specific oceanographic questions